How MasterSoft SIS Uses Agentic AI for Smart Decision-Making

Artificial intelligence has revolutionized the way organizations carry out their day-to-day operations, and the education sector has been among the primary beneficiaries. However, further innovation has led to agentic AI, an adaptable and autonomous technology that helps to establish a dynamic learning environment.

MasterSoft’s Student Information System incorporates agentic AI and helps to improve the education delivery methods and student learning experiences. But what is agentic AI? Let’s find out:

What is Agentic AI?

Agentic AI is an advanced artificial intelligence system that utilizes robust technological mechanisms such as machine learning, natural language processing (NLP), and large language models. In effect, it has the ability to understand its environment, make data-driven decisions, and take actions to attain specific outcomes.

Unlike traditional AI, agentic AI does not need particular prompts from the users and can identify problems, devise plans, and execute them effectively. Consequently, they can handle complex situations, gather necessary information from feedback, and adapt their responses and behavior gradually.

Leading ed-tech organizations like MasterSoft ERP Solutions have integrated the technology with their SIS software to ensure smart decision-making and improve efficiency in educational processes in the following ways:

1. Proactive Academic Intervention

Educational institutions strive for equitable educational opportunities and ensure progress for all their students; hence, offering timely support to struggling students is necessary. MasterSoft SIS utilizes Agentic AI to track behavioural metrics such as attendance, grades, assignment submission, participation in activities, etc.

At the same time, it identifies irregularities like frequent absenteeism, late assignment submissions, declining test scores, etc., and raises the issue by notifying relevant authoritative personnel. In effect, this creates an early warning system, allowing educators to offer appropriate support, like one-on-one tutoring, peer study groups, etc.

When educators and institutions offer appropriate support early on, it helps to prevent academic deterioration. Also, the technology does more than problem detection; it makes targeted recommendations based on students’ learning habits and behavior. For example, the system can suggest remedial classes for subjects based on students’ online active hours and the teacher’s availability.

2. Efficient Resource Optimization

Faculty and administrative workloads, scheduling conflicts, teachers’ unavailability, underutilization of resources, etc, are common issues. The software proves to be an ideal solution by facilitating smart resource planning.

It analyzes primary factors such as current timetables, class strength, historical patterns, and faculty availability and proposes optimized class schedules. This mechanism particularly helps to prevent faculty and staff workload and ensure that students don’t encounter timetable clashes, helping to foster a well-planned academic ecosystem.

Institutes can also get insights into future scenarios when the system simulates potential issues that can hinder operational efficiency. For example, the system can show how resources might be affected if a school or college expects an increase in the enrollment rate. Therefore, the agentic AI system can make suitable recommendations, like recruiting additional teachers for specific departments.

3. Intelligence Admission Forecasting

The online admission process automates the end-to-end enrollment steps, ensuring a smooth and hassle-free experience for both students and administrators. However, leveraging agentic AI-enabled SIS software can help determine application trends during the admission cycles.

The system examines current application behavior demographics, historical enrollment data, and past admission campaign performance to predict future outcomes. For example, it can forecast the courses and streams that will be in high demand and geographic regions or student profiles that will respond positively to particular programs and marketing efforts.

What’s more, the adjustable or intuitive forecasts provide insightful information. For instance, it suggests appropriate action plans like increasing seat availability if the mid-cycle data point towards an unexpected influx of applications. As a result, institutes can plan better, allocate resources properly, and avoid sudden procedural obstacles.

4. Curriculum and Assessment Development

An outdated and content-driven curriculum with little to no focus on outcome-based learning activities becomes an obstacle to effective education. That is where institutes can make use of the software system to scan the latest developments across different fields, industry trends, and academic trends to detect curriculum gaps.

If a certain batch of students fails to perform well in a subject or topic continuously, the agentic AI-enabled system can suggest modifications in the content. Furthermore, it can make recommendations for updating reading materials and resources and employing varying pedagogical strategies.

Also, the system proves to be the ultimate ed-tech tool as it helps educators to develop different kinds of assessments in regular classroom sessions. They can input learning objectives, which can prompt the AI to generate relevant exercises, activities, essays, and learning materials.

5. Risk Management

Operational efficiency relies on coordinated workflow, productivity, and risk management, which is why educational institutes must use agentic AI to evaluate risks. The software scans the system to detect inconsistencies and anomalies like overutilized labs, frequent late fee payments, etc., and notifies the specific departments.

Timely detection of such anomalies enables institutes to take targeted actions to lessen the negative impact and improve overall performance. Furthermore, the system recommends data-backed mitigation strategies and the anticipation of problems before their intensification, leading to informed decision-making.

For instance, in the case of delayed tuition fee payments, it can suggest introducing an installment-based payment option or auto-reminders. Likewise, it may suggest the redistribution of classes in case of underutilization of some classrooms.

6. Personalized Learning Pathways

One-dimensional educational approaches fail to cater to the learning needs and add value to students’ learning experiences. On the contrary, establishing personalized learning pathways by integrating the software system helps to determine varying learning styles and understanding levels.

Agentic AI detects students’ learning styles, strengths, and weaknesses by analyzing their past performances and then develops customized learning paths. It adjusts the content, depending on students’ learning activities, responses, and real-time interaction.

For instance, it offers simplified content and explanations for struggling students while increasing the content’s difficulty level for advanced students. Furthermore, the system provides personalized resource recommendations, including articles, videos, exercises, and interactive simulations that align with students’ interests.

Also, virtual tutors and AI-powered chatbots within the system offer additional assistance to students by providing answers and personalized feedback on their work. Teachers can develop adaptive assessments with the help of the tool, ensuring accurate evaluation of students’ understanding and ongoing progress.

7. Autonomous Decision-Making

Fragmented data makes it difficult for institute leaders to access information or get an overall view of students' academic journey and potential risks. Besides, unintegrated and separated systems lead to manual data entry and information exchange across departments.

That is where agentic AI-enabled SIS dashboards make all the difference by interpreting data trends, highlighting performance gaps, and recommending specific actions. For instance, if specific courses and programs lack consistent engagement and enrollment, the system may suggest corrective measures by corresponding curriculum engagement and feedback scores.

The system simulates various outcomes, including expected ROI and marketing requirements, helping to determine the benefits and drawbacks effectively